Applied Statistics for Life Sciences

Updated

January 16, 2025

Statistics plays a crucial role in the sciences: statistical techniques provide a means of weighing quantitative evidence derived from observation and experimentation while accounting for uncertainty. This class aims to provide a hands-on introduction to common statistical methods used almost universally across the sciences and a primer on statistical concepts. Examples from the life sciences emphasize applications with relevance to students’ majors, and students learn to perform simple analyses in R.

Read the [course syllabus] for more information.

Announcements

No class meetings week 3, but you do have a few responsibilities:

  • HW3 due Thursday 1/23
  • Test 1 will be a take home test available on Thursday 1/23 and due by 11:59pm PST. Check back for links.

Instructor: Trevor Ruiz (he/him) [email]

Learning assistant: Emi Degembe (she/they) [email]

Class meetings: 2:10pm — 4:00pm TR 005-225

Office hours and learning assistant hours:

Preparing for class meetings:

  1. Complete any problems or other work assigned with the previous class meeting; these should be submitted by the start of class.
  2. Check the course website for posted reading and materials. Readings should be skimmed in advance of class meetings and read in depth after class meetings.

Week 1 (1/6/25)

Tuesday: study design and data semantics

  • [reading] Vu and Harrington 1.1 - 1.3
  • [lecture] course intro; study designs and data semantics
  • [lab] R basics [solutions]

Thursday: descriptive statistics

  • [reading] Vu and Harrington 1.4 - 1.5
  • [lecture] descriptive statistics
  • [lab] descriptive statistics in R [solutions]
  • [HW1] due next class [prompts] [submit]

Week 2 (1/13/25)

Tuesday: point estimation

  • [reading] Vu and Harrington 4.1
  • [lecture] point estimation and sampling variability
  • [lab] point and interval estimation for a population mean [solutions]
  • [activity] enter your [armspan] in cm
  • [HW2] due next class [prompts] [submit]

Thursday: interval estimation

  • [reading] Vu and Harrington 3.3.1, 3.3.2, and 3.3.3; and 4.2
  • [lecture] confidence interval coverage and critical values
  • [lab] computing critical values [solutions]
  • [HW3] due Thursday 1/23 [prompts] [submit]

Week 3 (1/21/25)

MLK Jr. Day observed 1/20/25; Tuesday follows Monday schedule

Tuesday: no class meeting

Thursday: test 1 (take home) due 11:59pm PST

Week 4 (1/27/25)

Tuesday: inference for a population mean

  • [reading] Vu and Harrington 4.3.1 & 4.3.2

Thursday: one-sided alternatives

Week 5 (2/3/25)

Tuesday: two-sample inference

Thursday: statistical power

Week 6 (2/10/25)

Tuesday: nonparametric tests

Thursday: test 2

Week 7 (2/17/25)

Tuesday: analysis of variance (ANOVA)

Thursday: post-hoc inference

Week 8 (2/24/25)

Tuesday: inference for proportions

Thursday: tests of association

Week 9 (3/3/25)

Tuesday: relative risk and odds ratios

Thursday: test 3

Week 10 (3/10/24)

Tuesday: simple linear regression

Thursday: inference in regression

Exam info

Scheduled tests:

  • Test 1: Thursday 1/23/25 (week 3)
  • Test 2: Thursday 2/13/25 (week 6)
  • Test 3: Thursday 3/6/25 (week 9)
  • Final: Tuesday 3/18/25 4:10pm – 7:00pm

Study resources: